6 citations · 9 across the 13 of their papers we have counts for
8 papers · 1 filter
Mapping Written Words to Spoken Words in a Different Language Using Only Visual Grounding
Gabriel Pirlogeanu, Dan Oneata, Horia Cucu +1
In many low-resource settings, even just eliciting speech for data collection is difficult. One promising approach has been to ask speakers to describe images. But how do we build…
Self-supervised Speech Comparison for L2 Phone, Rhythm, and Intonation Scoring
Stephen McIntosh, Reuben Smit, Daisuke Saito +2
L2 speech assessment has traditionally focused on phonetic assessment, leaving the scoring of suprasegmental features such as rhythm and intonation underexplored. Moreover, assessm…
Visually Grounded Speech Models have a Mutual Exclusivity Bias
Leanne Nortje, Dan Oneaţă, Yevgen Matusevych +1
When children learn new words, they employ constraints such as the mutual exclusivity (ME) bias: a novel word is mapped to a novel object rather than a familiar one. This bias has…
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili
Christiaan Jacobs, Nathanaël Carraz Rakotonirina, Everlyn Asiko Chimoto +2
We consider hate speech detection through keyword spotting on radio broadcasts. One approach is to build an automatic speech recognition (ASR) system for the target low-resource la…
Visually grounded few-shot word acquisition with fewer shots
Leanne Nortje, Benjamin van Niekerk, Herman Kamper
We propose a visually grounded speech model that acquires new words and their visual depictions from just a few word-image example pairs. Given a set of test images and a spoken qu…
Mitigating Catastrophic Forgetting for Few-Shot Spoken Word Classification Through Meta-Learning
Ruan van der Merwe, Herman Kamper
We consider the problem of few-shot spoken word classification in a setting where a model is incrementally introduced to new word classes. This would occur in a user-defined keywor…